Age polyethism can emerge from social learning: A game-theoretic investigation
Age-polyethism-the age-based allocation of tasks in social insect colonies-is a key feature of division of labour. While its hormonal underpinnings have been studied extensively, the behavioural and environmental mechanisms driving age-polyethism remain poorly understood, especially under ecological stress. We present a novel modelling framework that integrates social learning with task-related environmental feedback to explain the emergence and breakdown of age-polyethism. We develop two models: a Social Learning (SL) model, in which individuals adapt task preferences by copying similar peers, and a Stimulus-Response Threshold Social Learning (SRT-SL) model, which extends this framework by incorporating task-related dynamic stimuli and response thresholds that regulate collective task demand. Our models demonstrate that age-polyethism can emerge from simple social imitation processes, without the need for fixed hormonal schedules. We show that under increasing environmental pressure (e.g., resource scarcity), age-polyethism collapses as younger individuals are forced into tasks typically handled by older workers. Importantly, we find that age-polyethism does not necessarily optimize immediate colony efficiency; instead, it appears to reflect a trade-off between environmental constraints and behavioural coordination. These findings provide a mechanistic and ecologically grounded explanation for empirical observations linking environmental stress to dysfunctional division of labour and colony collapse.
Authors
- M. Amin Khajehnejad (ORCID: https://orcid.org/0000-0002-2185-4596)
- Julián García (ORCID: https://orcid.org/0000-0001-9639-489X)
- Bernd Meyer (ORCID: https://orcid.org/0000-0003-1080-0338)
Institutions
- Monash University (AU)
Publication Details
- Journal
- PLoS Computational Biology
- Published
- 2025-08-25
- DOI
- https://doi.org/10.1371/journal.pcbi.1013415
- Primary Topic
- Insect and Arachnid Ecology and Behavior
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Australian Research Council